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The Application of Convolutional Neural Network Model in Diagnosis and Nursing of MR Imaging in Alzheimer's Disease

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Abstract

The disease Alzheimer is an irrepressible neurologicalbrain disorder. Earlier detection and proper treatment of Alzheimer’s disease can help for brain tissue damage prevention. The study was intended to explore the segmentation effects of convolutional neural network (CNN) model on Magnetic Resonance (MR) imaging for Alzheimer's diagnosis and nursing. Specifically, 18 Alzheimer's patients admitted to Indira Gandhi Medical College (IGMC) hospital were selected as the experimental group, with 18 healthy volunteers in the Ctrl group. Furthermore, the CNN model was applied to segment the MR imaging of Alzheimer's patients, and its segmentation effects were compared with those of the fully convolutional neural network (FCNN) and support vector machine (SVM) algorithms. It was found that the CNN model demonstrated higher segmentation precision, and the experimental group showed a higher clinical dementia rating (CDR) score and a lower mini-mental state examination (MMSE) score (P < 0.05). The size of parahippocompalgyrus and putamen was bigger in the Ctrl (P < 0.05). In experimental group, the amplitude of low-frequency fluctuation (ALFF) was positively correlated with the MMSE score in areas of bilateral cingulum gyri (r = 0.65) and precuneus (r = 0.59). In conclusion, the grey matter structure is damaged in Alzheimer's patients, and hippocampus ALFF and regional homogeneity (ReHo) is involved in the neuronal compensation mechanism of hippocampal damage, and the caregivers should take an active nursing method.

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Acknowledgements

Wuhan education and science project “The Application of Convolutional Neural Network Model in Diagnosis and Nursing of MR Imaging in Alzheimer's disease” in Applied-Oriented Universities Taking Wuhan Business University. Author would also like to thank Indira Gandhi Medical College for allowing the experimental group of AD patients.

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Authors and Affiliations

  1. Department of Neurology, Zhuji affiliated hospital of Shaoxing University, Shaoxing, Zhejiang province, 311800, China

    Xiaoxiao Chen & Linghui Li

  2. Institute of Computer Technology and Information Security, Southern Federal University, Rostov Oblast, Russia

    Ashutosh Sharma

  3. Department of Computer Science, Government Bikram College of Commerce, Punjab, India

    Gaurav Dhiman

  4. Department of CSE, Ramco Institute of Technology, Rajapalayam, Tamilnadu, India

    S. Vimal

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  1. Xiaoxiao Chen
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Correspondence to Linghui Li.

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Chen, X., Li, L., Sharma, A. et al. The Application of Convolutional Neural Network Model in Diagnosis and Nursing of MR Imaging in Alzheimer's Disease. Interdiscip Sci Comput Life Sci 14, 34–44 (2022). https://doi.org/10.1007/s12539-021-00450-7

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